Untitled
unknown
plain_text
15 days ago
1.5 kB
3
Indexable
import base64 from PIL import Image import io # Assuming `response_json['image']` contains the base64 string image_data = base64.b64decode(response_json['image']) image = Image.open(io.BytesIO(image_data)) image.show() # device2_server.py from flask import Flask, request, jsonify from PIL import Image import io import cv2 import numpy as np import model_det2 app = Flask(__name__) @app.route('/process-image', methods=['POST']) def process_image(): file = request.files['image'] image = Image.open(file.stream).convert('RGB') # Ensure it's RGB # Convert PIL image to OpenCV format image_np = np.array(image) cv2.imshow("raw", cv2.resize(image_np, None, fx=0.25, fy=0.25)) cv2.waitKey(100) # Do your image processing here, return list of values #values = ["value1", "value2", "value3"] im1, obbs, classes, conf = model_det2.recognise_det2(image_np) cv2.imshow("ann", cv2.resize(im1, None, fx=0.25, fy=0.25)) cv2.waitKey(100) #return jsonify(classes) # Convert im1 (OpenCV image) to base64 string _, buffer = cv2.imencode('.jpg', im1) im1_bytes = buffer.tobytes() im1_base64 = base64.b64encode(im1_bytes).decode('utf-8') return jsonify({ 'image': im1_base64, 'obbs': obbs, 'classes': classes, 'conf': conf }) if __name__ == '__main__': app.run(host='0.0.0.0', port=5000) # Expose on local network
Editor is loading...
Leave a Comment